Triple
T7461901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Cats |
E176269
|
entity |
| Predicate | showcasesAspect |
P61123
|
FINISHED |
| Object | animal behavior |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: animal behavior | Statement: [Great Cats, showcasesAspect, animal behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showcasesAspect Context triple: [Great Cats, showcasesAspect, animal behavior]
-
A.
coversAspect
chosen
Indicates that one entity addresses, includes, or deals with a particular aspect or facet of another entity or topic.
-
B.
presentAspect
Indicates that an action, state, or event is occurring in the present time frame, often with ongoing or current relevance.
-
C.
helpedShowcase
Indicates that one entity actively assisted in presenting, promoting, or displaying another entity to an audience.
-
D.
symbolicAspect
Indicates that one entity functions as a symbol or emblem that represents, expresses, or conveys a particular meaning, quality, or concept of another entity.
-
E.
showsThat
Indicates that one entity demonstrates, proves, or provides evidence for the truth or validity of another.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d6cf8c8190a31cac121d151d78 |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:38 p.m.